Sparse Zero Correlation Zone Arrays for Training Design in Spatial Modulation Systems

This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and c...

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Vydáno v:	IEEE transactions on communications Ročník 73; číslo 11; s. 10277 - 10289
Hlavní autoři:	Pai, Cheng-Yu, Liu, Zilong, Chen, Chao-Yu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.11.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Arrays Boolean functions Broadband antennas Channel estimation Channels Controllability Cross correlation Delays Interference Kernel Modulation restricted extended generalized Boolean function (REGBF) restricted generalized Boolean function (RGBF) Selective fading Simulation Sparse matrices Sparse zero correlation zone (SZCZ) arrays spatial modulation (SM) Training training matrix design Zero correlation zone
ISSN:	0090-6778, 1558-0857
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Abstract	This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and cross-correlation zone properties across any two rows. With these unique properties, we show that SZCZ arrays can be effectively used as training matrices for SM systems. Additionally, direct constructions of SZCZ arrays with large ZCZ widths and controllable sparsity levels based on 2D restricted extended generalized Boolean functions (REGBFs) are proposed. Compared with existing training schemes, the proposed SZCZ-based training matrices have larger ZCZ widths, thereby offering greater tolerance for delay spread in multipath channels. Simulation results demonstrate that the proposed SZCZ-based training design exhibits superior channel estimation performance over frequency-selective fading channels compared to existing alternatives.
AbstractList	This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and cross-correlation zone properties across any two rows. With these unique properties, we show that SZCZ arrays can be effectively used as training matrices for SM systems. Additionally, direct constructions of SZCZ arrays with large ZCZ widths and controllable sparsity levels based on 2D restricted extended generalized Boolean functions (REGBFs) are proposed. Compared with existing training schemes, the proposed SZCZ-based training matrices have larger ZCZ widths, thereby offering greater tolerance for delay spread in multipath channels. Simulation results demonstrate that the proposed SZCZ-based training design exhibits superior channel estimation performance over frequency-selective fading channels compared to existing alternatives.
Author	Pai, Cheng-Yu Liu, Zilong Chen, Chao-Yu
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SubjectTerms	Arrays Boolean functions Broadband antennas Channel estimation Channels Controllability Cross correlation Delays Interference Kernel Modulation restricted extended generalized Boolean function (REGBF) restricted generalized Boolean function (RGBF) Selective fading Simulation Sparse matrices Sparse zero correlation zone (SZCZ) arrays spatial modulation (SM) Training training matrix design Zero correlation zone
Title	Sparse Zero Correlation Zone Arrays for Training Design in Spatial Modulation Systems
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